Journal Article10.1177/026119291404200505
Statistical methods and software for validation studies on new in vitro toxicity assays.
TL;DR: Confidence intervals for predictive values are computed for a validation study of an in vitro test battery, and sample size calculation is illustrated for an acute toxicity assay using R, the free software.
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Abstract: When a new in vitro assay method is introduced, it should be validated against the best available knowledge or a reference standard assay. For assays resulting in a simple binary outcome, the data can be displayed as a 2×2 table. Based on the estimated sensitivity and specificity, and the assumed prevalence of true positives in the population of interest, the positive and negative predictive values of the new assay can be calculated. We briefly discuss the experimental design of validation experiments and previously published methods for computing confidence intervals for predictive values. The application of the methods is illustrated for two toxicological examples, by using tools available in the free software, namely, R: confidence intervals for predictive values are computed for a validation study of an in vitro test battery, and sample size calculation is illustrated for an acute toxicity assay. The R code necessary to reproduce the results is given.
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Hermann Brenner,Olaf Gefeller +1 more
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Confidence intervals for predictive values with an emphasis to case-control studies.
TL;DR: A novel method for the estimation of PPV and NPV, as well as their confidence intervals, is developed and is applied to two case–control studies: a diagnostic test assessing the ability of the e4 allele of the apolipoprotein E gene (ApoE) on distinguishing patients with late‐onset Alzheimer's disease (AD) and a prognostic test assessingThe predictive ability of a 70‐gene signature on breast cancer metastasis.
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Sample size for positive and negative predictive value in diagnostic research using case–control designs
TL;DR: Formulas for optimal allocation of the sample between the case and control cohorts and for computing sample size when the goal of the study is to prove that the test procedure exceeds pre-stated bounds for PPV and/or NPV are developed.
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